Volumetric Conjoint
The next generation of choice-based conjoint analysis delivers a new and innovative way to predict changes in product volume.
STEVE COHEN – Choice modeling is a type of conjoint analysis used to help researchers identify the utility of different product features, benefits, values, and costs. There have been many key advancements in the application of conjoint analysis, however, one important aspect of how consumers make purchase decisions has been largely ignored — how many units of a product or service they will buy.
This article looks at the development of volumetric data in conjoint analysis.
Volumetric Conjoint
Volumetric conjoint is an advanced modeling technique that measures how many units consumers would buy based on the product attributes they are offered. It allows companies to understand how product changes might impact purchase volume, sales, and revenue.
The ability to include volumetric data in conjoint analysis gives a competitive edge when it comes to product development and pricing. Volumetric data is information that assesses not just preference but also how much of a product or service consumers will purchase at different prices and with different features. It can be used to determine whether a product is priced competitively, whether it should offer additional features, and how much production is needed to meet demand.
Volumetric conjoint can be applied in a wide variety of situations for different products, services, and industries. Examples include a bottle of Coke, a can of peas, a pound of grapes, or a pack of cigarettes.
Product Volume
Volumetric conjoint is a great way to investigate how buyers in certain situations will respond to the volume of products that are available to purchase.
Research shows that when there is greater variety and selection at the point of purchase, there will be an increase in the volume purchased. The implication for volumetric conjoint is that rather than having choice sets of the same size to display to buyers, the researcher must design studies that include situations with varying numbers of products to capture potential changes in volume. Designing studies with varying choice set sizes is not trivial, but certainly can and should be done when executing volumetric choice studies.
Pricing
With volumetric conjoint, we can also determine how much more or less of a product consumers would purchase based on price.
For example, we might be interested in how people buying beer would respond if they were presented with different pricing options for beer in varying package sizes. If the consumer must choose between a 6-pack for $8 or a 24-pack for $18, what is the most likely choice? With volumetric conjoint, we can determine which pack they prefer and whether they are willing to pay more for additional bottles — even if they don’t necessarily need it.
We assume that people will want to buy the most for their money but will not buy beyond their budget. We also assume that people cannot continue to buy more and more, but at some time their volume or count will begin to increase, and they will “satiate.” That’s the point at which buyers are paying more per bottle of beer but are getting fewer bottles. They are getting less value from this purchase and will likely switch to another alternative. So, when we design our studies, we need to consider how much volume or count people buy at various prices.
When volume, weight, or count is an important part of pricing, traditional CBCA methods will not provide enough data for key decision-making. Instead, volumetric conjoint must be applied to obtain the independent role of price and volume/weight in these situations.
Applying Volumetric Conjoint to Your Business
The use of conjoint analysis over the years has been proven to be a valuable marketing tool, as it predicts not only what new products consumers will want, but also potential impacts on volume and revenue. Volumetric conjoint is a new and exciting development that will revolutionize your research and allow you to understand your customer like never before. If this sounds like an area that could help your business, please contact me today – Schedule a call or Send an email.
About Steve Cohen 
Steve Cohen is an award-winning entrepreneur, specializing in design of research, analysis of marketing data, and using marketing science tools to solve business problems. In 1984, Steve was the first commercial researcher to do choice-based conjoint and subsequently, he authored the first conference presentation and paper on MaxDiff. He is a co-author of the first academic paper on Latent Class Choice-based Conjoint and Menu-based Conjoint. Steve was won numerous awards for his research including: AMA “Parlin” Award, INFORMS Society for Marketing Science “Buck Weaver” Award, NextGen Marketing Research Disruptive Innovator Award, NY Marketing Research Council’s Hall of Fame, ESOMAR Goodyear Award for the Best International Research Paper, AMA Hardin Award for the Best Paper in Marketing Research Magazine, and Best Presentation at Sawtooth Software Conference. Read More
